Study identifies potential benefits of the Advanced Quantitative Precipitation Information system for the San Francisco Bay

Photo of sandbags.Flood damages can be mitigated by early warning and protective measures.
Flood damages can be mitigated by early warning and protective measures. Photo credit: FEMA

When big storms hit California, detailed information is needed to inform water and emergency managers. NOAA and collaborating partners are developing an Advanced Quantitative Precipitation Information (AQPI) system for the San Francisco Bay area to help improve early warning and enhance public safety when hazardous weather comes onshore. In a new study to be published in the Journal of Flood Risk Management, CIRA and NOAA researchers from the Physical Sciences Division performed a regional study to identify the benefits associated with AQPI. Their method used established procedures and available data, and examined benefits associated with avoided flood damages, maximizing water supplies, and enhancement of ecological, recreational and transportation services. The total incremental benefits were estimated to be $61M per year.

The calculations translate to a cumulative 10-year value benefit of $449M, which computes to a best estimate benefit-to-cost ratio of 5 to 1. Sensitivity analysis indicates a range of benefit-to-cost up to 10 and down to 2. Taken by category, about 48% of the total benefits are for flood damage mitigation ($29M/yr), with water supply (32%, $19.5M/yr), ecosystem (3.3%, $2M/yr), recreation (7.6%, $4.6M/yr), and transportation (9.5%, $5.8M/yr). Many of the benefits are dependent on appropriate and adequate response by hazards and water management agencies and citizens.

Decisions to invest in an operational AQPI system required demonstration of economic feasibility. This study shows that AQPI would provide substantial benefits with incrementally higher resolution monitoring of rainfall events and longer lead-time forecasts compared to current practice.

Authors of 'Benefits of an Advanced Quantitative Precipitation Information System' are: Lynn Johnson, Rob Cifelli, and Allen White of PSD.